The extraction of this interesting information is a very challenging task.
Once measured, the signal is mapped onto a vector containing effective and discriminant features from the observed signals. The feature extraction stage identifies discriminative information in the brain signals that have been recorded. The preprocessing stage prepares the signals in a suitable form for further processing. The signal acquisition stage captures the brain signals and may also perform noise reduction and artifact processing. Such an interface would improve their quality of life and would, at the same time, reduce the cost of intensive care.Ī BCI is an artificial intelligence system that can recognize a certain set of patterns in brain signals following five consecutive stages: signal acquisition, preprocessing or signal enhancement, feature extraction, classification, and the control interface. That is particularly attractive for individuals with severe motor disabilities. BCI creates a new non-muscular channel for relaying a person's intentions to external devices such as computers, speech synthesizers, assistive appliances, and neural prostheses.
CHRIS COLE PCLP SOFTWARE
Keywords: brain-computer interface (BCI) electroencephalography (EEG) rehabilitation artifact neuroimaging brain-machine interface collaborative sensor systemĪ brain computer interface (BCI), also referred to as a brain machine interface (BMI), is a hardware and software communications system that enables humans to interact with their surroundings, without the involvement of peripheral nerves and muscles, by using control signals generated from electroencephalograph^ activity. Finally, the review provides an overview of various BCI applications that control a range of devices. Fourth, the review studies some mathematic algorithms used in the feature extraction and classification steps which translate the information in the control signals into commands that operate a computer or other device. Third, the review includes some techniques used in the signal enhancement step to deal with the artifacts in the control signals and improve the performance. Second, the review discusses different electrophysiological control signals that determine user intentions, which can be detected in brain activity. First, the review examines the neuroimaging modalities used in the signal acquisition step, each of which monitors a different functional brain activity such as electrical, magnetic or metabolic activity.
We discuss their advantages, drawbacks, and latest advances, and we survey the numerous technologies reported in the scientific literature to design each step of a BCI. Here, we review the state-of-the-art of BCIs, looking at the different steps that form a standard BCI: signal acquisition, preprocessing or signal enhancement, feature extraction, classification and the control interface. The immediate goal of BCI research is to provide communications capabilities to severely disabled people who are totally paralyzed or 'locked in' by neurological neuromuscular disorders, such as amyotrophic lateral sclerosis, brain stem stroke, or spinal cord injury. Received: 29 December 2011 in revised form: 16 January 2012 / Accepted: 29 January 2012 /Ībstract: A brain-computer interface (BCI) is a hardware and software communications system that permits cerebral activity alone to control computers or external devices. Luis Fernando Nicolas-Alonso * and Jaime Gomez-Gilĭepartment of Signal Theory, Communications and Telematics Engineering, University of Valladolid,